Showing papers in "Journal of Informetrics in 2017"

TL;DR: This paper proposes a unique open-source tool, designed by the authors, called bibliometrix, for performing comprehensive science mapping analysis, programmed in R, and can be rapidly upgraded and integrated with other statistical R-packages.

TL;DR: The results show that GS has significantly expanded its coverage through the years which makes it a powerful database of scholarly literature, however, the quality of resources indexed and overall policy still remains known.

TL;DR: Evidence is found that Google Scholar ranks those documents whose language (or geographical web domain) matches with the user’s interface language higher than could be expected based on citations, however, this language effect and other factors related to the Google Scholar operation only have an incidental impact.

TL;DR: It is shown that only collaboration at intramural and domestic level has a positive effect on research productivity, and all the forms of collaboration are positively affected by research productivity.

TL;DR: Mendeley reader counts were more precise than Scopus citations for the most recent articles and all three funders could be demonstrated to have an impact in Wikipedia that was significantly above the world average.

TL;DR: A new method to construct the knowledge network using article keywords and empirically examine the hypotheses of the relationships between node attributes of two networks and the paper’s citations, which fill the gap in prior studies and will inspire related studies.

TL;DR: The results suggest that working with leading experts can lead to a successful career, but that it is not the only way, and that researchers who were not fortunate enough to start their career with an elite researcher could still succeed through hard work and passion.

TL;DR: Examination of how research topics evolve by analyzing the topic trends, evolving dynamics, and semantic word shifts in the IR domain shows that the evolution of a major topic usually follows a pattern from adjusting status to mature status, and sometimes with re-adjusting status in between the evolving process.

TL;DR: It is shown that if output based research funding has an effect on research quality, it is positive and not negative, as in those debates the Australian case plays a major role.

TL;DR: The results show that research performance differences among universities mainly stem from size, disciplinary orientation and country location, which suggests that simple global benchmarking can be misleading.

TL;DR: It is shown, quantitatively, that the regularity in the authorship contributions decreases with the number of authors in a paper, and that authors in the intermediary positions of the rank contribute more in specific roles, such as collecting data.

TL;DR: In this article, the authors used a large data set with many thousands of publication profiles of individual researchers to test the ability of the JIF (in its normalized variant) to identify, at the beginning of their careers, those candidates who will be successful in the long run.

TL;DR: A new indicator of topic prominence is presented – a measure of visibility, momentum and, ultimately, demand – that explains over one-third of the variance in current (or future) funding by topic.

TL;DR: A structured discussion of the VQR 2011–2014 is presented, collecting and organizing some critical arguments so far emerged, and developing them in detail.

TL;DR: It is found that in the Polish system, not all the collected data are necessary to achieve the main goal of the system, namely the categorization of scientific units in terms of their research performance.

TL;DR: A procedure for identifying discoveries in the biomedical sciences is described that makes use of citation context information, or more precisely citing sentences, drawn from the PubMed Central database, and reveals the types of words and concepts that scientists associate with discoveries.

TL;DR: In this paper, the authors used percentile shares to analyze so-called "factors influencing citation impact" (FICs; e.g., the impact factor of the publishing journal) across years and disciplines and found that the correlation between FICs and citation impact is lower if citations are normalized instead of using raw citation counts.

TL;DR: The use of metaknowledge is motivated to scale efficiently for analyzing very large datasets, and the design and core functionality of the package are explained.

TL;DR: A way to recommend relevant, specialized scholarly venues using these implicit ratings that can provide quick results, even for new researchers without a publication history and for emerging scholarly venues that do not yet have an impact factor is presented.

TL;DR: The hypothesis that patent citations can indicate knowledge linkage, which is the basic assumption of the patent citation analysis method, is accepted.

TL;DR: Analyzing a large citation network of authors based on almost two million computer science papers and applying four PageRank-based and citations-based techniques to rank authors by importance throughout the period 1990–2014, it is concluded that citations- based rankings perform better for Codd Award winners, but Page Rank-based methods do so for Turing Award recipients when using absolute ranks.

TL;DR: This paper addresses software citation by analyzing how R and its packages are cited in a sample of PLoS papers, and considers citations of the core R software environment, of specific R packages, and of individual functions.

TL;DR: In this article, the authors use a large citation dataset from Microsoft Academic Graph and a new statistical framework based on the Mahalanobis distance to show that the rankings by well known indicators, including the relative citation count and Google's PageRank score, are significantly biased by paper field and age.

TL;DR: A list of intellectual activities and logistic support activities that might be involved in the production of a research paper is proposed and a quantitative approach to estimate an author’s relative intellectual contribution to a published work is developed.

TL;DR: A new criterion for choosing between a pair of classification systems of science that assign publications (or journals) to a set of clusters is proposed, considering the standard target (citedside) normalization procedure in which cluster mean citations are used as normalization factors.

TL;DR: A scientometric analysis of the 30 neuroscience journals with the highest impact in the Web of Science database (Thomson Reuters) in order to quantitatively examine the current contribution of women in neuroscientific production, their pattern of research collaboration, scientific content, and the analysis of scientific impact from a gender perspective suggests that age probably plays a role in (partly) explaining gender asymmetry.

TL;DR: A novel computational methodology based on unsupervised machine learning that can act as an important tool at the hands of evaluation committees of individual scholars and can also be employed for the profiling of scholar groups is proposed.

TL;DR: It is found that Weibo users discuss global science, more actively compared with several international altmetrics sources, and the common motivation of scientific weibos is to disseminate or discuss the articles because they are interesting, surprising, academically useful or practically useful.

TL;DR: In this paper, the authors report the largest and most systematic analysis so far, of 172,752 articles in 29 large journals chosen from different specialisms from Scopus citation counts, Microsoft Academic citation counts and Mendeley reader counts for articles published 2007-2017.

TL;DR: It is shown, based on 16,000 journals containing ~2.4 million articles, that the citation success index is a relatively tight function of the ratio of IFs of journals being compared, due to the fact that journals with same IF have quite similar citation distributions.